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DBMS > EXASOL vs. Google Cloud Bigtable vs. Quasardb vs. Solr

System Properties Comparison EXASOL vs. Google Cloud Bigtable vs. Quasardb vs. Solr

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.exasol.comcloud.google.com/­bigtablequasar.aisolr.apache.org
Technical documentationwww.exasol.com/­resourcescloud.google.com/­bigtable/­docsdoc.quasar.ai/­mastersolr.apache.org/­resources.html
DeveloperExasolGooglequasardbApache Software Foundation
Initial release2000201520092006
Current release3.14.1, January 20249.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedBSD
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyes infointeger and binaryyes infosupports customizable data types and automatic typing
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononoyes
Secondary indexesyesnoyes infowith tagsyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesJava
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnonoJava plugins
Triggersyesnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyeswith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient modeyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Cryptographically strong user authentication and audit trailyes

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More resources
EXASOLGoogle Cloud BigtableQuasardbSolr
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